Address
Form of work
SalaryGCP ML Data Engineer
Fulltime Role
100% Remote
Summary:
We are seeking a highly motivated and experienced GCP ML Data Engineer to join our team and play a pivotal role in developing and implementing Data Engineering solutions for our artificial intelligence (AI) and Machine learning (ML) initiatives on the Google Cloud Platform (GCP). The ideal candidate will possess a deep understanding of Data Engineering principles, cloud computing, and ML algorithms, and will be passionate about leveraging data to drive business value.
Key Responsibilities:
- Data Acquisition and Integration:
- Collaborate with data scientists and business stakeholders to identify and gather relevant data sources for ML projects.
- Develop and implement data ingestion pipelines using GCP tools and services, such as Cloud Dataflow, Cloud Pub/Sub, and BigQuery.
- Ensure data quality and consistency by performing data cleaning, transformation, and validation.
- Data Preprocessing and Feature Engineering:
- Apply data preprocessing techniques, such as data normalization, encoding, and feature selection, to prepare data for ML models.
- Extract meaningful features from raw data to enhance model performance and interpretability.
- Data Labeling and Annotation:
- Coordinate with data labeling teams or utilize ML-assisted labeling tools to generate labeled datasets for supervised learning tasks.
- Ensure the accuracy and consistency of data labels to minimize errors and biases in ML models.
- Cloud Infrastructure Management:
- Provision and manage GCP cloud infrastructure, including virtual machines, containers, and storage systems, to support Data Engineering and ML workloads.
- Optimize cloud resource utilization and costs through efficient resource allocation and monitoring.
- Model Training and Evaluation:
- Collaborate with ML engineers to train and evaluate ML models using GCP AI services, such as Cloud Machine Learning Engine and BigQuery ML.
- Monitor model performance metrics and identify opportunities for improvement.
- Data Visualization and Reporting:
- Develop data visualization dashboards and reports to communicate data insights and ML model performance to technical and non-technical stakeholders.
- Knowledge Sharing and Collaboration:
- Document Data Engineering processes and best practices, and share knowledge with the broader team to foster a culture of innovation.
- Collaborate with cross-functional teams, including data scientists, ML engineers, and product managers, to deliver end-to-end AI solutions.
Required Skills and Qualifications:
- Bachelor’s degree or equivalent experience in Computer Science, Data Science, or a related field.
- Minimum of five years of experience in Data Engineering, with a focus on cloud-based data management and processing.
- Strong programming skills in Python and proficiency with GCP data tools and services, such as BigQuery, Cloud Dataflow, and Cloud Storage.
- Experience with data preprocessing, feature engineering, and data labelling techniques for ML.
- Familiarity with ML algorithms and model evaluation metrics.
- Excellent problem-solving skills and a strong analytical mindset.
- Strong communication skills, both written and verbal, with the ability to explain technical concepts to non-technical stakeholders.
- Ability to work independently and as part of a team in a fast-paced, dynamic environment.
- Passion for Data Engineering and its potential to drive business value through AI and ML.
Job Type: Full-time
Pay: $101,373.86 - $122,084.65 per year
Benefits:
- 401(k)
- Dental insurance
- Health insurance
Schedule:
- 8 hour shift
Work Location: Remote
